Carbon estimator
Skill navveenb/lean-agentic-ai/lean-agentic-ai-claude-implementation/.claude/skills/carbon-estimator
Lean Agentic AI
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Estimate the carbon footprint of an agentic AI system based on its LLM usage
SKILL.md
2.6 KB, 714 tokens by cl100k_base, as published. Nobody here has run it
Carbon Estimator
Estimate the CO₂ emissions of an agentic system based on model usage, call volume, and deployment region.
Lean Principle
- #6 Emissions don't show up in your logs
Instructions
Step 1: Gather inputs
From the user or from context, determine:
- Daily LLM call volume (or estimate from code scan)
- Model distribution (% small, % medium, % frontier)
- Deployment region (or assume US Average if unknown)
Step 2: Calculate energy
Use these energy-per-call estimates:
| Model Size | Energy per Call (kWh) |
|---|---|
| Small (Haiku, GPT-4o-mini, Flash) | 0.001 |
| Medium (Sonnet, GPT-4o, Pro) | 0.005 |
| Frontier (Opus, GPT-4, o1, Ultra) | 0.03 |
Total daily energy (kWh) =
(small_calls × 0.001) + (medium_calls × 0.005) + (frontier_calls × 0.03)
Step 3: Calculate carbon
Use these regional carbon intensities (gCO₂/kWh):
| Region | gCO₂/kWh |
|---|---|
| Quebec / Norway / Iceland | 25 |
| France / Sweden | 70 |
| US West (Oregon) | 100 |
| Netherlands / UK | 200 |
| US Average | 380 |
| Germany | 350 |
| India | 700 |
| Poland / Coal regions | 800 |
Daily CO₂ (grams) = Total daily energy × Regional carbon intensity
Annual CO₂ (kg) = Daily CO₂ × 365 / 1000
Step 4: Calculate optimized scenario
Assume lean optimizations:
- Model routing: shift 60% of frontier calls to medium, 30% of medium calls to small
- Caching: 30% cache hit rate (reduces total calls by 30%)
- Green region: use the cleanest available region (25 gCO₂/kWh)
Recalculate with these optimizations applied.
Step 5: Write report
Write to reports/carbon-estimate.md with:
- Current estimated annual CO₂ (kg)
- Optimized estimated annual CO₂ (kg)
- Reduction percentage
- Human-relatable equivalents:
- Cars driven for a year (÷ 4,600 kg)
- Flights (÷ 255 kg per domestic flight)
- Phone charges (÷ 0.008 kg per charge)
- Top recommendation
Example
Input: 50,000 calls/day, 70% medium, 30% frontier, deployed in US Average.
Output:
Current: 50K calls/day → 212.5 kWh/day → 80.75 kg CO₂/day → 29,474 kg/year
Equivalent: ~6.4 cars driven for a year
Optimized: 35K calls/day (caching) → 28 kWh/day (routing) → 0.7 kg CO₂/day (green region) → 256 kg/year
Equivalent: ~1 domestic flight
Reduction: 99.1%
Top recommendation: Move batch workloads to Quebec (25 gCO₂/kWh)
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.